Machine Learning in Drug Discovery and Development Part 1: A Primer
Alan Talevi, Juan Francisco Morales, Gregory Hather, Jagdeep T. Podichetty, Sarah Kim, Peter Bloomingdale, Samuel Kim, Jackson K. Burton, Joshua David Brown, Almut Gertrud Winterstein, Stephan Schmidt, Jensen Kael White, Daniela J. Conrado · CPT Pharmacometrics & Systems Pharmacology · 2020
Artificial intelligence, in particular machine learning (ML), has emerged as a key promising pillar to overcome the high failure rate in drug development. Here, we present a primer on the ML algorithms most commonly used in drug discovery and development. We also list possible data sources, describe good practices for ML model development and validation, and share a reproducible example. A companion article will summarize applications of ML in drug discovery, drug development, and postapproval phase.